Comments (4)
Hi Luan,
I fixed the issue. Now once you run “pip install seg-metrics --upgrade”, you can run you original code even you used the “~” sign in your path.
from segmentation_metrics.
Hi Luan,
Sorry for the late reply.
- Normally the reason of the issue is that the file names of two folders are different. So the program did not know which prediction corresponded to which ground truth. Please check if you set the file name correctly.
- It seems that you would like to calculate 20 pairs of cases, right? Then, you need to put 20 binary prediction to one folder, and put the other 20 binary ground truth to another folder. Note: the file names should be the same between the two folders. For instance, "prediction/1.nii, prediction/2.nii, ..." and "ground_truth/1.nii, ground_truth/2.nii, ..."
labels = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
this line may be wrong. Because the labels should be[0,1]
for binary image metrics calculation.0
means backgournd and1
means foreground if your ground truth and prediction is binarized with 0 and 1.
If you still have question please let me know.
from segmentation_metrics.
Hi Jingnan,
I did it !! That was the problem "~". (as you told me)
Thank you very much for everything.
Best,
Luan.
from segmentation_metrics.
Hi Jingnan,
Thank you very much !!!
from segmentation_metrics.
Related Issues (17)
- URGENT: Great package, your myutil.py script not included in pip/git version HOT 1
- AttributeError: module 'numpy' has no attribute 'Array' HOT 1
- TypeError: 'type' object is not subscriptable, line 144 HOT 2
- Import error HOT 6
- Adding TP TN FP FN HOT 5
- Open-source collaboration
- Code is not working for different cronology in labels HOT 3
- Unit of Volume Similarity HOT 4
- Type error issue when using this package with Pytest HOT 1
- Logging issues HOT 1
- Add .png suffix HOT 2
- Adding .dcm contour data
- Computing values on ground truth does not give perfect scores HOT 5
- Evaluation metric 3D or 2D based segmentation
- what will be the input labels for the function of 'get_metrics_dict_all_labels'?
- Potential Documentation Optimization
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